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Transportation Dissertation
| Title | Fuzzy Logic Transit Preemption Signal Controller: Genetic Algorithm and Ant Colony Optimization Approaches |
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| Year | 2006 |
| Summary | Transit preemption signal (TPS) is to give transit vehicles, such as trams and buses, passing through the signalized intersections on surface roads with preferential treatment. The reduction of overall delays in transit moving direction, however, can be offset by the increase of overall delays at the competing approaches. Without a vigilant design, the negative impacts to the vehicles at competing approaches might outweigh the benefits to the vehicles in transit moving direction. Therefore, appropriate design of the control mechanism becomes an important issue if one intends to introduce such preferential scheme to favor the transit operation.
This study develops novel TPS control models based on Genetic Fuzzy Logic Controller (GFLC) and Ant-Genetic based Fuzzy Logic Controller (AGFLC), respectively. These models consider the traffic conditions at the signalized intersection to minimize the total person delay. Due to the powerful ability of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) for solving hard combinational optimization problems, the GFLC and AGFLC models are able to automatically equip a FLC with the compromising fuzzy rules and membership functions. To examine the proposed models, TPS strategies including green extension and red truncation are implemented at an isolated intersection and at two consecutive intersections along an arterial. Studies on an exemplified example with sensitivity analyses and a field case are conducted, respectively, both under the isolated intersection and the arterial. The simulation results at the isolated intersection reveal that the proposed GFLC and AGFLC conditional TPS models perform better than unconditional TPS and the AGFLC performs even better than GFLC. As for the sensitivity analyses, both the GFLC and AGFLC models perform better in low traffic than in high traffic. Moreover, green extension strategy performs better than red truncation strategy as traffic increases. When bus loading factor gets higher, the performance of the GFLC and AGFLC models would be enhanced. In the field case study, the proposed GFLC and AGFLC still perform better than unconditional TPS. Furthermore, the simulation results of studies on the two consecutive intersections along an arterial show that implementing TPS under progressive coordinated signal system would have the best performance, followed by simultaneous system and then by alternate system. The results of performance comparisons, sensitivity analyses, and field case study are similar to those at the isolated intersection. In conclusion, the simulation results suggest that the proposed GFLC and AGFLC models are effective, robust, and applicable to implement TPS at an isolated intersection and at two consecutive intersections along an arterial. |
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